1. Introduction to data analysis: Case studies with iSIKHNAS data Day 1 1/ 69

2. Introduction to course Relevance of data analysis to policy Objectives of course Pre-requisites

3. Learning approach

4. Steps in data analysis Objective Data management Descriptive analysis Hypothesis testing

5. Key concepts for sampling (1) Sampling verse census Bias Sampling variability

6. Key concepts for sampling (2) Datasets and variables

7. Key concepts for sampling (3) Distributions

8. Case study 1: Introduction

9. Case study 1: Objectives Objectives – Exercise 1 – Exercise 2

10. Case study 1: Data management Download iSIKHNAS data Preserve data

11. Key concepts on errors Missing data – Blank cells in data – Missing observations Incorrect data – Random errors – Systematic errors

12. Case study 1: Data management Exercises 3: Missing data Exercise 5: Create new data

13. Key concepts on descriptive statistics Variable types Continuous variables – Measures of central tendency – Measures of dispersion

14. Case study 1: Description of data Exercise 6: Descriptive statistics Exercise 6b: Descriptive statistics without analysis ToolPak Exercise 7: Plotting (histograms)

15. Summary of case study 1

16. The end of day 1